Accurate monitoring of plant dust retention can provide a basis for dust pollution control and environmental protection. The aims of this study were to analyze the spectral response features of grassland plants to mining dust and to predict the spatial distribution of dust retention using hyperspectral data. The dust retention content was determined by an electronic analytical balance and a leaf area meter. The leaf reflectance spectrum was measured by a handheld hyperspectral camera, and the airborne hyperspectral data were obtained using an imaging spectrometer. We analyzed the difference between the leaf spectral before and after dust removal. The sensitive spectra of dust retention on the leaf- and the canopy-scale were determined through two-dimensional correlation spectroscopy (2DCOS). The competitive adaptive reweighted sampling (CARS) algorithm was applied to select the feature bands of canopy dust retention. The estimation model of canopy dust retention was built through random forest regression (RFR), and the dust distribution map was obtained based on the airborne hyperspectral image. The results showed that dust retention enhanced the spectral reflectance of leaves in the visible wavelength but weakened the reflectance in the near-infrared wavelength. Caused by the canopy structure and multiple scattering, a slight difference in the sensitive spectra on dust retention existed between the canopy and leaves. Similarly, the sensitive spectra of leaves and the canopy were closely related to dust and plant physiological parameters. The estimation model constructed through 2DCOS-CARS-RFR showed higher precision, compared with genetic algorithm-random forest regression (GA-RFR) and simulated annealing algorithm-random forest regression (SAA-RFR). Spatially, the amount of canopy dust increased and then decreased with increasing distance from the mining area, reaching a maximum within 300–500 m. This study not only demonstrated the importance of extracting feature bands based on the response of plant physical and chemical parameters to dust, but also laid a foundation for the rapid and non-destructive monitoring of grassland plant dust retention.

Ground subsidence is the main cause of vegetation degradation in mining areas. It is of great significance to study the effects of ground subsidence on vegetation. At present, few studies have analyzed the effects of ground subsidence on vegetation from different scales. However, the conclusions on different scales may differ. In this experiment, chlorophyll content was used as an indicator of vegetation degradation. We conducted a long-term field survey in the Lijiahao coalfield in China. Based on field survey data and remote sensing images, we analyzed the effects of ground subsidence on chlorophyll content from two scales (leaf scale and canopy scale) and summarized the similarities and differences. We found that, regardless of leaf scale or canopy scale, the effects of subsidence on chlorophyll content have the following three characteristics: (1) mining had the least effect on chlorophyll content in the neutral area, followed by the compression area, and the greatest effect on chlorophyll content in the extension area; (2) subsidence had a slight effect on chlorophyll content of Caragana korshins, but a serious effect on chlorophyll content of Stipa baicalensis; (3) chlorophyll content was not immediately affected when the ground sank. It was the cumulative subsidence that affects chlorophyll content. The difference between leaf scale and canopy scale was that the chlorophyll content at canopy scale is more affected by mining. This means that when assessing vegetation degradation, the results obtained by remote sensing were more severe than those measured in the field. We believe that this is because the canopy chlorophyll content obtained by remote sensing is also affected by the plant canopy structure. We recommend that mining and ecological restoration should be carried out concurrently, and that ground fissures should be taken as the focus of ecological restoration. In addition, Caragana korshins ought to be widely planted. Most importantly, managers should assess the effects of ground subsidence on vegetation on different scales. However, managers need to be aware of differences at different scales.